The present invention will be useful for evaluating and detecting pathologies that impact mental and cardiac health. It is known that vagal influence on the heart rate is reduced during a depressive state and that beat-to-beat (btb) dynamics and vagal balance are in-turn influenced by cardiac function.
A quantitative assessment of depressive state has application in clinical trials and in management of depressive disorder. Current means of assessing depressive state involve the use of questionnaires such as the Beck Depression Inventory [1]. Subjectivity of responses often leads to a high degree of error in measured result vs. actual clinical effect. No technique is currently available that can provide a reliable quantitative assessment of depressive state.
Assessment of cardiac ischemia, including myocardial infarction (MI), is important in clinical research and clinical care. Current means of assessing cardiac ischemia include the use of a 12 lead ECG to measure ST segment elevation. This test is performed under both stressed and unstressed conditions in the clinic. Ischemia and MI, however, are often transient and are triggered by mental stress and other stimuli as the patient goes about their normal every day activities. It therefore can be useful to assess ischemia and MI on ambulatory patients as they go about their normal activities.
Measurement of ST segment elevation is sometimes performed on continuous ECG recordings (i.e. Holter) to non-invasively assess ischemia in ambulatory patients, but noise and artifact render accurate measurements difficult. There is no technique available that provides an accurate non-invasive assessment of cardiac ischemia or detection of MI in ambulatory subjects.
Prediction and detection of heart failure decompensation is useful in medical management of patients with heart failure as detection can prompt care providers to intervene early and prevent hospitalization. Current non-invasive techniques to assess heart failure decompensation in ambulatory patients include daily measurement of weight and patient self-assessment. Sensitivity and specificity of existing techniques is poor and hence the rate of avoidable hospitalizations is excessive.